Di Li
Impact in
- Applied Psychology top 10%
- Digital Mental Health Interventions
- Artificial Intelligence top 5%
- AI in Service Interactions
- Topic Modeling
- Speech and dialogue systems
- Natural Language Processing Techniques
- Sentiment Analysis and Opinion Mining
- Anomaly Detection Techniques and Applications
Papers in
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- Anomaly Detection Techniques and Applications 2
- Domain Adaptation and Few-Shot Learning 2
- Speech and dialogue systems 1
- AI in Service Interactions 1
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- Video Surveillance and Tracking Methods 3
- Face and Expression Recognition 1
- Advanced Vision and Imaging 1
- Co-authors
- Xiaodong He (1 shared paper)Heung‐Yeung Shum (1 shared paper)Liang Song (2 shared papers)Yang Liu (2 shared papers)Dingkang Yang (1 shared paper)Hao Yang (1 shared paper)Chong Wang (1 shared paper)Jing Liu (1 shared paper)
- Journals
- Sensors (1 paper)IEEE Transactions on Multimedia (1 paper)IEEE Transactions on Circuits and Systems for Video Technology (1 paper)Expert Systems with Applications (1 paper)Pattern Analysis and Applications (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Di Li
6 papers receiving 440 citations
Di Li's Hit Papers
Peers
Comparison fields: 5 of 62
- Applied Psychology 57
- Artificial Intelligence 337
- Health Informatics 10
- Human-Computer Interaction 21
- Social Psychology 69
Countries citing papers authored by Di Li
This map shows the geographic impact of Di Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Di Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Di Li more than expected).
Fields of papers citing papers by Di Li
This network shows the impact of papers produced by Di Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Di Li. The network helps show where Di Li may publish in the future.
Co-authors
The 12 scholars most cited alongside Di Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | From Eliza to XiaoIce: challenges and opportunities with social chatbots Hit paper breakdown → | 2018 | 405 |
| 2 | 2024 | 16 | |
| 3 | 2022 | 16 | |
| 4 | 2024 | 11 | |
| 5 | 2022 | 5 | |
| 6 | 2024 | 2 |
About Di Li
Di Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Civil and Structural Engineering and Social Psychology, having authored 6 papers that have together received 455 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (3 papers), Anomaly Detection Techniques and Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Social Robot Interaction and HRI (1 paper), Speech and dialogue systems (1 paper), Face and Expression Recognition (1 paper), AI in Service Interactions (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Applied Psychology (57 citations), Artificial Intelligence (337 citations), Health Informatics (10 citations), Human-Computer Interaction (21 citations) and Social Psychology (69 citations). Di Li has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Xiaodong He, Heung‐Yeung Shum, Liang Song, Yang Liu, Dingkang Yang, Hao Yang, Chong Wang, Jing Liu, Jiangbo Qian and Peng Sun. Their work appears in journals such as Sensors, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, Expert Systems with Applications and Pattern Analysis and Applications.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.